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Scaling Up Concurrent Main-Memory Column-Store Scans

Scaling Up Concurrent Main-Memory Column-Store Scans

陈傲天
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Main-memory column-stores are called to efficiently use modern non-uniform memory access (NUMA) architectures to service concurrent clients on big data. The efficient usage of NUMA architectures depends on the data placement and scheduling strategy of the column-store. Most column-stores choose a static strategy that involves partitioning all data across the NUMA architecture, and employing a stealingbased task scheduler.
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